The Impact of Generative Artificial Intelligence Dependency on Cognitive Function of University Students: A Cross-Sectional Study.
This observational cross-sectional study aims to investigate the relationship between dependence on generative artificial intelligence (AI) tools and cognitive functioning among university students.
Study Overview
Status
Conditions
Intervention / Treatment
Detailed Description
The increasing integration of generative artificial intelligence (GenAI) into higher education has transformed how university students access information, understand academic concepts, and complete learning activities. Although these technologies offer educational benefits, excessive dependence on AI-generated responses may be associated with cognitive offloading and reduced engagement in independent thinking and problem-solving.
This study aims to examine the association between generative AI dependency and cognitive functioning among university students, with particular attention to cognitive domains such as attention, memory, and executive functioning.
An observational cross-sectional design will be employed. Eligible university students aged 18-25 years will be invited to participate voluntarily through online announcements and electronic survey links. Informed consent will be obtained before data collection.
Participants will complete a structured online questionnaire collecting demographic and academic information, patterns of generative AI use, dependency-related responses, and measures of cognitive functioning.
The collected data will be analyzed using descriptive statistics, correlation analysis, and regression analysis to explore the relationship between AI dependency and cognitive functioning.
As this is a cross-sectional observational study, the results will identify possible associations but will not establish a causal relationship between generative AI dependency and changes in cognitive functioning.
The findings may contribute to understanding the educational implications of generative AI dependency and inform future research and teaching strategies promoting responsible AI use.
Study Type
Enrollment (Estimated)
Contacts and Locations
Study Contact
- Name: Sara Abdullah mohamed, PhD
- Phone Number: +20 11 51401438
- Email: sara.samahi@must.edu.eg
Study Locations
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Giza, Egypt
- Faculty of Physical Therapy, Misr University for Science and Technology (MUST)
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Contact:
- Sara Abdullah mohamed, PhD
- Phone Number: +20 11 51401438
- Email: sara.samahi@must.edu.eg
-
-
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
The study population will include university students aged 18-25 years who use generative artificial intelligence (AI) tools for academic or daily activities. Eligible participants will be recruited from selected universities through electronic announcements, institutional emails, and online survey links. Participation will be voluntary, and informed consent will be obtained before completing the questionnaires assessing generative AI dependency and cognitive functioning.
Description
Inclusion Criteria:
- Enrolled undergraduate or graduate university students.
- Active users of digital devices and generative AI tools for academic or daily tasks.
- Ages between 18 and 25 years.
- Provided informed consent to participate in the study.
Exclusion Criteria:
- Diagnosed neurological or psychiatric disorders known to affect cognitive function.
- History of severe traumatic brain injury.
- Concurrent use of central nervous system-active medications that significantly alter cognitive performance.
- Incomplete questionnaire submissions.
Study Plan
How is the study designed?
Design Details
- Observational Models: OTHER
- Time Perspectives: CROSS_SECTIONAL
Cohorts and Interventions
Group / Cohort |
Intervention / Treatment |
|---|---|
|
University Students
This cohort will include university students aged 18-25 years who use generative artificial intelligence (AI) tools. Participants will complete self-administered questionnaires assessing their level of generative AI dependency and cognitive functioning. Data will be collected at a single point in time to examine the association between these variables. No intervention will be administered. |
No Intervention: Observational Cohort |
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Generative AI Dependency
Time Frame: At enrollment (single assessment)
|
Measured via a validated Generative AI Dependency Scale or Questionnaire. |
At enrollment (single assessment)
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Cognitive Function
Time Frame: At enrollment (single assessment)
|
Assessed using standardized self-reported or validated neuropsychological instruments focusing on specific domains such as attention, memory, and executive function. |
At enrollment (single assessment)
|
Collaborators and Investigators
Investigators
- Principal Investigator: Sara Abdullah mohamed, PhD, Lecturer, MUST University
Study record dates
Study Major Dates
Study Start (Estimated)
Primary Completion (Estimated)
Study Completion (Estimated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Other Study ID Numbers
- PT. BU. EC. 50
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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